• Bandaru kirankumar
• Dr.A.sri.nagesh

The proliferation of deepfake technology has raised concerns about the spread of misinformation on social media platforms. In this paper, we propose a deep learning-based approach for detecting deepfake tweets, specifically those generated by machines, to help mitigate the impact of misinformation online. Our approach leverages FastText embeddings to represent tweet text and combines them with deep learning models for classification. We first preprocess the tweet text and then use FastText embeddings to convert them into dense vector representations. These embeddings capture semantic information about the tweet content, which is crucial for distinguishing between genuine and machine-generated tweets. We then feed these embeddings into a deep learning model, such as a Convolutional Neural Network (CNN) or a Long Short-Term Memory (LSTM) network, to classify the tweets as genuine or machine-generated. The model is trained on a labeled dataset of tweets, where machine-generated tweets are synthesized using state-of-the-art text generation models. Experimental results on a real-world dataset of tweets demonstrate the effectiveness of our approach in detecting machine-generated tweets. Our approach achieves high accuracy and outperforms existing methods for deepfake detection on social media. Overall, our proposed methodology offers a robust and effective solution for detecting machine-generated tweets and curbing the proliferation of misinformation across social media platforms.

Deepfake detection, deep learning, FastText embeddings, machine-generated tweets, misinformation, social media, tweet classification

"Deepfake Detection on Social Media: Leveraging Deep Learning and FastText Embeddings for Identifying Machine-Generated Tweets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.f777-f784, July-2024, Available :http://www.jetir.org/papers/JETIR2407598.pdf

"Deepfake Detection on Social Media: Leveraging Deep Learning and FastText Embeddings for Identifying Machine-Generated Tweets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. ppf777-f784, July-2024, Available at : http://www.jetir.org/papers/JETIR2407598.pdf